Commit 8a248461 authored by Jamal KHAN's avatar Jamal KHAN

Fix formatting exo1

parent ddbddbbe
#+TITLE: On the computation of pi
#+TITLE: On the computation of pi
#+LANGUAGE: en
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="http://www.pirilampo.org/styles/readtheorg/css/htmlize.css"/>
......@@ -8,7 +8,7 @@
#+HTML_HEAD: <script type="text/javascript" src="http://www.pirilampo.org/styles/lib/js/jquery.stickytableheaders.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="http://www.pirilampo.org/styles/readtheorg/js/readtheorg.js"></script>
#+PROPERTY: header-args :eval never-export
#+PROPERTY: header-args :session :exports both
* Asking the maths library
My computer tells me that $\pi$ is /approximatively/
......@@ -23,7 +23,7 @@ pi
* Buffon's needle
Applying the method of [[https://en.wikipedia.org/wiki/Buffon%2527s_needle_problem][Buffon's needle]], we get the *approximation*
#+begin_src R :results output :session *R* :exports results
#+begin_src R :results output :session *R* :exports both
set.seed(42)
N = 100000
x = runif(N)
......@@ -35,7 +35,7 @@ theta = pi/2*runif(N)
: [1] 3.14327
* Using a surface fraction argument
A method that is easier to understand and does not make use of the $\sin$ function is based on the fact that if $X\simU(0,1)$ and $Y\simU(0,1)$, then $P[X^2+Y^2 \le1]=\pi/4$ (see [[https://en.wikipedia.org/wiki/Monte_Carlo_method]["Monte Carlo method" on Wikipedia]]). The following code uses this approach:
A method that is easier to understand and does not make use of the $\sin$ function is based on the fact that if $X\simU(0,1)$ and $Y\simU(0,1)$, then $P[X^2+Y^2\leq 1] = \pi/4$ (see [[https://en.wikipedia.org/wiki/Monte_Carlo_method]["Monte Carlo method" on Wikipedia]]). The following code uses this approach:
#+begin_src R :results output graphics :file figure_pi_mc1.png :exports both :width 600 :height 400 :session *R*
set.seed(42)
......@@ -43,13 +43,13 @@ N = 1000
df = data.frame(X = runif(N), Y = runif(N))
df$Accept = (df$X**2 + df$Y**2 <=1)
library(ggplot2)
ggplot(df, aes(x=X, y=Y, color=Accept)) + geom_point(alpha=.2) + coord_fixed() + theme_bw()
ggplot(df, aes(x=X,y=Y,color=Accept)) + geom_point(alpha=.2) + coord_fixed() + theme_bw()
#+end_src
#+RESULTS:
[[file:figure_pi_mc1.png]]
It is then straightforward to obtain a (not really good) approximation to \pi by counting how many times, on average, $X^2 + Y^2$ is smaller than 1:
It is then straightforward to obtain a (not really good) approximation to $\pi$ by counting how many times, on average, $X^2 + Y^2$ is smaller than 1:
#+begin_src R :results output :session *R* :exports both
4*mean(df$Accept)
#+end_src
......
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